
Highdimensional Bayesian model selection by proximal nested sampling
Imaging methods often rely on Bayesian statistical inference strategies ...
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Slepian ScaleDiscretised Wavelets on the Sphere
This work presents the construction of a novel spherical wavelet basis d...
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Paying Attention to Astronomical Transients: Photometric Classification with the TimeSeries Transformer
Future surveys such as the Legacy Survey of Space and Time (LSST) of the...
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Bayesian variational regularization on the ball
We develop variational regularization methods which leverage sparsitypr...
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Sparse image reconstruction on the sphere: a general approach with uncertainty quantification
Inverse problems defined naturally on the sphere are becoming increasing...
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Reducing cybersickness in 360degree virtual reality
Despite the technological advancements in Virtual Reality (VR), users ar...
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Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs
Convolutional neural networks (CNNs) constructed natively on the sphere ...
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Multiscale Optimal Filtering on the Sphere
We present a framework for the optimal filtering of spherical signals co...
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Sifting Convolution on the Sphere
A novel spherical convolution is defined through the sifting property of...
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Online radio interferometric imaging: assimilating and discarding visibilities on arrival
The emerging generation of radio interferometric (RI) telescopes, such a...
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Uncertainty quantification for radio interferometric imaging: II. MAP estimation
Uncertainty quantification is a critical missing component in radio inte...
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Uncertainty quantification for radio interferometric imaging: I. proximal MCMC methods
Uncertainty quantification is a critical missing component in radio inte...
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WaveletBased Segmentation on the Sphere
Segmentation is the process of identifying object outlines within images...
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Jason D. McEwen
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